class_docstr: Constructs a Speech2Text processor which wraps a Speech2Text feature extractor and a Speech2Text tokenizer into a
  single processor.
  
  [`Speech2TextProcessor`] offers all the functionalities of [`Speech2TextFeatureExtractor`] and
  [`Speech2TextTokenizer`]. See the [`~Speech2TextProcessor.__call__`] and [`~Speech2TextProcessor.decode`] for more
  information.
  
  Args:
      feature_extractor (`Speech2TextFeatureExtractor`):
          An instance of [`Speech2TextFeatureExtractor`]. The feature extractor is a required input.
      tokenizer (`Speech2TextTokenizer`):
          An instance of [`Speech2TextTokenizer`]. The tokenizer is a required input.
docstr: This method forwards all its arguments to Speech2TextTokenizer's [`~PreTrainedTokenizer.batch_decode`]. Please
  refer to the docstring of this method for more information.
docstr_tok: ["This","method","forwards","all","its","arguments","to","Speech2TextTokenizer","'s","[","`","~PreTrainedTokenizer.batch_decode","`","]",".","Please","refer","to","the","docstring","of","this","method","for","more","information","."]
code: def batch_decode(self, *args, **kwargs):
      """
      This method forwards all its arguments to Speech2TextTokenizer's [`~PreTrainedTokenizer.batch_decode`]. Please
      refer to the docstring of this method for more information.
      """
      return self.tokenizer.batch_decode(*args, **kwargs)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/speech_to_text/processing_speech_to_text.py
imports: import warnings
  from contextlib import contextmanager
  from ...processing_utils import ProcessorMixin
label_desc: Use image node_id 3 for calling the Speech2TextProcessor obj's underlying member method code with example usage: obj.batch_decode() and returns: self